Digital Marketing Strategy and Consumer Behavior Analysis Through Deep Q-Network (DQN) Models

Understanding digital client behaviour is essential for marketing optimisation in today's corporate environment. This study examines how online information searches, social media involvement, e-commerce buying patterns, and content consumption affect consumer behaviour. The study examines how data-driven decision-making, targeted social media advertising, tailored content, and enhanced e-commerce platforms can boost marketing. The suggested strategy involves data preparation and model training. The study highlights choosing the optimal data preprocessing methods to improve model performance. A Double Deep Q-Network (DDQN) model predicted customer behaviour after data preprocessing. The DDQN model outperformed ANN and SVM models with 93.07% accuracy. This study underlines how complex neural networks improve consumer behaviour model predicting. The findings highlight the necessity for tailored digital strategies to boost marketing efficiency and engagement across digital platforms.